Term
Ethical AI
Definition
Ethical AI involves making sure that artificial intelligence (AI) systems are created and operated in a way that is fair, transparent, and respects both individual and societal rights.
Where you’ll find it
Ethical AI principles are part of the design, development, and deployment stages of AI systems. These principles are often outlined in the documentation or guidelines of AI platforms, showing the platform's commitment to responsible AI use.
Common use cases
- Developing AI models: Ensuring that the data used is free from biases and that the models do not inadvertently discriminate.
- Deploying AI solutions: Regularly reviewing AI systems to ensure they comply with ethical standards and adapt to new ethical guidelines as they arise.
- User Interaction: Implementing features that enable users to understand and question AI decisions, such as why they were shown a particular ad or content.
Things to watch out for
- Bias in data: Incorrect or biased data can lead an AI to make unfair decisions.
- Lack of transparency: Users should be able to understand how and why an AI system made a specific decision.
- Over-reliance: Depending too much on AI can sometimes reduce human empathy or overlook nuanced human contexts.
Related terms
- AI Transparency
- Data Privacy
- Responsible AI
- Machine Learning
- AI Governance
Pixelhaze Tip: Always involve a diverse team when setting up or reviewing your AI systems. This helps spot potential biases or ethical concerns that might not be evident to everyone.